Lecture by Juliane Britz: (Micro-) states of consciousness Alteration of resting-state network dynamics during loss of consciousness

The EEG topography is a global measure of the momentary brain state, and its configuration remains stable for brief periods (~70 – 100 ms), the so- called EEG microstates. One characteristic feature of EEG microstates is the rapid transition from one stable scalp field topography into another. Using simultaneous EEG/fMRI, we previously identified EEG microstates as the electrophysiological correlate of four fMRI resting state networks [1]. This link could be established because the EEG microstates are mono-fractal and show long-range temporal correlations from tenths of seconds to tens of seconds [2], i.e. their sequence follows clearly defined rules without being predictable, analogous to how natural languages follow a generative grammar. This is the key feature that permits the brain to rapidly adjust to unexpected events and to successfully interact with the environment, which can be considered as a necessary prerequisite for consciousness.

In addition, we addressed how the scale-free properties of the EEG microstate sequences change with pharmacologically induced loss of consciousness (LOC) during the step-wise induction of general anesthesia with Propofol. At every effect-site concentration, we measured 5 minutes of resting-state EEG along with a clinical assessment of consciousness (OAA/S score). A cluster analysis identified the canonical microstate patterns, and their long-range temporal correlations varied with the depth of anesthesia: it decreased at intermediate levels of OAA/S scores and increased again when fully unconscious, which reflects differences in the distributions of their dwell times.

I will discuss these results in terms of how critical dynamics change with loss of consciousness and in terms of an electrophysiological marker of the transition to unconsciousness.